3 Disclaimer This report has been reviewed by the Office of Air Qualtiy Planning and Standards, U.S. Environmental Protection Agency, and has been approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. Acknowledgments The Agency wishes to acknowledge AERMIC (the American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee), members of which have given a considerable amount of time, energy and dedication over the last 10 years to develop the AERMOD air dispersion modeling system: W.D. Peters, U.S. Environmental Protection Agency, OAQPS, EMAD,AQMG A. Venkatram, College of Engineering, University of California at Riverside J. C. Weil, Cooperative Institute for Research in Environmental Sciences, University of Colorado R. B. Wilson, U.S. Environmental Protection Agency, Region X R. J. Paine, ENSR Corporation S.G. Perry 1, Atmospheric Sciences Modeling Division, Air Resources Laboratory, EPA/ NOAA R. F. Lee, Consultant, Meteorologist A. J. Cimorelli, U.S. Environmental Protection Agency, Region III In addition, Mr. Roger Brode of MACTEC Federal Programs, Inc. (formerly known as Pacific Environmental Services Inc) has provided considerable talent and support to the AERMOD project and has conducted many analyses over the last several years to test and develop this new air dispersion model. 1 On assignment to the Atmospheric Research and Exposure Assessment Laboratory, U.S. Environmental Protection Agency.

5 1. INTRODUCTION 1.1 Background information. This report is a final version of an earlier consequence analysis 2, which was released to support the proposal of AERMOD (the American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee s Dispersion Model, version 99351) in a Federal Register notice 3 on April 21, At that time, the EPA also proposed an additional model, ISC-PRIME ( Industrial Source Complex -Short Term Model[Version 3] - Plume RIse Model Enhancements), designed to be used in cases where building downwash was significant; AERMOD was to be used for air pollution source scenarios where downwash was not an issue. To support the ISC-PRIME proposal, there was a separate but similar buildingdownwash-consequence analysis completed which compared ISC-PRIME to ISCST3 4 (Industrial Source Complex -Short Term Model--Version 3). Responding to the overwhelming reaction from the commenters on the proposal, the Agency decided to incorporate PRIME algorithms into AERMOD and thereby eliminate the use of the ISC-PRIME model. The final results in this report consider both downwash and non-downwash source scenarios since AERMOD now provides the state of the science for modeling both types of source scenarios. Thus, this report is designed to supercede the two earlier consequence analyses. This analysis is based on the lastest version of AERMOD, version , which includes the PRIME algorithms and the proposed version of AERMOD (99351). The ISC-PRIME results are based on version 99020; the ISCST3 results are based on version (for the downwash analysis) and version (for the point, area and volume sources) which are the same versions of the models used in the earlier consequence analyses. The introduction includes the following additional sections: a description and purpose of a consequence analysis; a description of the 3 components to this study; and, a brief description of the air dispersion models of interest - AERMOD (including a list of AERMOD changes since the proposal), ISCST3, ISC-PRIME, and, CTDMPLUS (the Complex Terrain Dispersion Model- Plus). 1.2 What is a consequence analysis? The purpose of this report, often called a consequence analysis, is to give the user community a sense of how regulatory design concentrations from a new air dispersion model compare to those from an established model via a series of representative examples. After the release of a new model for regulatory applications, the user community will want to know: What does this mean to my modeling projects?. This analysis is designed to answer that question by 2 Peters,W.D. et al, Comparison of Regulatory Design Concentrations: AERMOD versus ISCST3 and CTDMPlus, draft document, April 1999, available on the EPA website: 3 Federal Register notice, 65FR21506, April 21, Paine, R.J. and Lew, F., Consequence Analysis for Adoption of PRIME: an Advanced Building Downwash Model, August 24, 1998, available on the EPA website: 5 Available on the EPA website: 4

6 showing the effects of the new model as compared to the existing regulatory model which it replaces. For this study, the new model is AERMOD with the PRIME algorithms. The existing regulatory models used in this report are ISCST3, ISC-PRIME, and CTDMPLUS. This consequence analysis does not substitute for detailed comparative evaluations or sensitivity analyses, but rather, provides to the modeler some simple comparisons of regulatory design concentration estimates from these air quality models for an extensive number of typical source scenarios. 1.3 The three components of this study. There are three parts to this study: the flat and simple terrain component; the building downwash component; and, the complex terrain component. The building downwash component has been added to the original report since AERMOD now contains the PRIME building downwash feature and will be used for sources near buildings. All of the study components use source scenarios and meteorological data sets which remain unchanged from the earlier consequence analyses. The flat and simple terrain consequence analysis is based on comparative runs made using a composite of standard data sets. These data sets include a range of point sources with varying stack parameters, area and volume sources, and two point sources in simple terrain 6. All source scenarios are evaluated with two meteorological data sets representing different climatic regimes in the U.S. For building downwash, a series of point sources with varying stack heights and different building configurations are included in the data sets. Only one of the meteorological data sets used in the previous description is used in this part of the analysis. For the complex terrain, the study includes a number of stack heights, buoyancy regimes, distances from source to hill, and hill types along with its own meteorological data base (one site). After applying the model to all of the above source scenarios, the consequence analysis is summarized by tabulating the important regulatory (design) concentrations for the new model against those predicted by the existing regulatory models. Often, the concentrations of regulatory interest are the high and the high-second-highest concentrations for 1-hour, 3-hour, 24-hour, and annual averages, and they are used in this study. The choice of averaging times is based on the earlier consequence analyses, although this choice is not consistent across all three components of this study. 1.4 A Brief Description of AERMOD 7. A committee, AERMIC (the American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee), was formed to introduce state-of-the-art modeling concepts into the EPA s local-scale air quality models. AERMIC's focus was on a new platform for regulatory steady-state plume modeling; this platform would include air dispersion 6 Simple terrain includes receptors with elevations below the top of the stack and at elevations above or below the stack base. Intermediate terrain includes receptors with elevations above stack top and below the plume centerline. Complex terrain includes receptors with elevations above the top of the stack. 7 User s Guide for the AMS/EPA Regulatory Model - AERMOD, US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, Report No EPA-454/B , July Available on the EPA website: 5

7 fundamentally based on planetary boundary layer turbulence structure, scaling and concepts. AERMOD is designed to treat both surface and elevated sources in simple and complex terrain. Special features of AERMOD include its ability to treat the vertical inhomogeneity of the planetary boundary layer, special treatment of surface releases, irregularly-shaped area sources, a three-plume model for the convective boundary layer, and limitation of vertical mixing in the stable boundary layer. A treatment of dispersion in the presence of intermediate and complex terrain is used that improves on that treatment currently in use in ISCST3 and other models, yet without the complexity of a model such as CTDMPLUS. AERMOD incorporates, with a new simple approach, current concepts about flow and dispersion in complex terrain. Where appropriate, the plume is modeled as either impacting and/or following the terrain. This approach is designed to be physically realistic and simple to implement while avoiding the need to distinguish among simple, intermediate and complex terrain, as is required by present regulatory models. As a result, AERMOD removes the need for defining complex terrain regimes; all terrain is handled in a consistent and continuous manner that is simple while still considering the dividing streamline concept in stably-stratified conditions. AERMOD is actually a modeling system with three separate components: AERMOD (AERMIC Dispersion Model), AERMAP (AERMOD Terrain Preprocessor), and AERMET (AERMOD Meteorological Preprocessor). AERMET is the meteorological preprocessor for AERMOD. Input data can come from hourly cloud cover observations, surface meteorological observations and twice-a-day upper air soundings. Output includes surface meteorological observations and parameters and vertical profiles of several atmosheric parameters. AERMAP is a terrain preprocessor designed to simplify and standardize the input of terrain data for AERMOD. Input data include receptor terrain elevation data. The terrain data may be in the form of digital terrain data that is available from the U.S. Geological Survey. For each receptor, the output includes a location and height scale, which is an elevation used for the computation of air flow around hills. Additional information about AERMOD can be found in other documents. The model evaluation paper 8 compares both AERMOD (proposed and current versions), CTDMPLUS, ISCST3's and ISC-PRIME s model predictions against measured ambient concentrations. The Model Formulation Document 9 provides a detailed explanation of the science behind the model. 8 USEPA, AERMOD: Latest features and Evaluation Results. Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, EPA Report No. EPA-454/R July Available on the EPA website: 9 USEPA, AERMOD: Description of Model Formulation (Version 02222), Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, EPA Report No. EPA-454/R , October Available on the EPA website: 6

8 The AERMOD, AERMET and AERMAP User s Guides 7,10,11 inform the user community about the various options and features of the model and its preprocessors. 1.5 Changes made to AERMOD since the proposal A summary of the changes made to the AERMOD in response to comments include the following: * adding the PRIME algorithms to the model (response to public comments); * modifying the complex terrain algorithms to make AERMOD less sensitive to the selection of the domain of the study area (response to public comments); * modifying the urban dispersion for low-level emission sources, such as area sources, to produce a more realistic urban dispersion and, as a part of this change, changing the minimum layer depth used to calculate the effective dispersion parameters for all dispersion settings (scientific formulation correction which was requested by beta testers); and making an adjustment to the friction velocity and the Monin-Obukhov length for urban stable cases (improved scientific formulation); * upgrading AERMOD to include all the newest features that exist in the latest version of ISC such as FORTRAN 90 compliance and allocatable arrays, EVENTS processing and the TOXICS option (response to public comments). In doing the follow-up quality control checking of the model and the source code, the need for additional changes were identified and the following changes have been made: * adding meander to: 1) the stable and unstable urban and 2) the rural unstable dispersion settings (only the rural, stable dispersion setting considered meander in the earlier version of AERMOD - this change provides a consistent treatment of air dispersion in all dispersion settings); * making some changes to the basic meander algorithms (improved scientific formulation); * making a correction to avoid elevated concentrations for terrain below stack base from the virtual image source (response to public comments about spurious results in complex terrain); and, * repairing miscellaneous coding errors. A more detailed list of corrections are given in the model evaluation paper Overview of ISCST USEPA, User s Guide for the AERMOD Meteorological Preprocessor (AERMET), US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, EPA Report No EPA-454/B , July Available on the EPA website: 11 USEPA, User s Guide for the AERMOD Terrain Preprocessor (AERMAP), US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, EPA Report No EPA-454/B , August Available on the EPA website: 12 USEPA, User s Guide for the Industrial Source Complex (ISC3) Dispersion Models, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, Report No. EPA-454/B a, September Available on the EPA website: 7

9 ISCST3 is especially designed to support the EPA's regulatory modeling programs. This model is a steady-state Gaussian dispersion model with a number of options available to the user. These options include the use of stack-tip downwash, buoyancy-induced dispersion, final plume rise (except for sources with building downwash), a routine for processing averages when calm winds occur, and default values for wind profile exponents and for the vertical potential temperature gradients. The Short Term model also incorporates COMPLEX1 screening model dispersion algorithms for receptors in complex terrain. The user may select either rural or urban dispersion parameters, depending on the characteristics of the source location. A more detailed side-by-side explanation and comparison of features between ISCST3 and AERMOD is given in Appendix A. 1.7 Overview of PRIME. PRIME was developed by the Electric Power Research Institute to provide new and improved plume rise and building downwash algorithms. The PRIME set of algorithms was incorporated into ISCST3 and the new model was called ISC-PRIME. The improved algorithms provided the following new features:. consideration of the location of the stack in relationship to the building;. consideration of the streamline deflection over the building;. inclusion of plume rise affected by the velocity deficit in the wake or vertical wind speed shear;. a linkage between plume material captured by the near wake and far wake concentrations;. elimination of discontinuities at the interface between the two downwash algorithms;. provision of wind direction effects for squat buildings;. elimination of the large concentrations predicted by ISCST3 during light wind speed, stable conditions that are not supported by observations. A further, more detailed, description of the model 13 and the evaluation results 14 are available. 1.8 A Brief Description of CTDMPLUS 15. CTDMPLUS is a refined Gaussian plume dispersion model designed to estimate hourly concentrations of plume material from elevated point sources at receptors on or near isolated terrain features. This model can assess stable and neutral atmospheric conditions as well as daytime, unstable conditions. Its use of meteorological data and terrain information is different from other regulatory models in that considerable detail for both types of input data is required and is supplied by preprocessors specifically designed for CTDMPLUS. 13 L.L. Schulman, D.G. Strimaitis, J.S. Scire, Development and Evaluation of the PRIME Plume Rise and Building Downwash Model, Jounrnal of Air and Waste Management Association, 50: , March R.J. Paine, F. Lew, Results of of the Independent Evaluation of ISCST3 and ISC-PRIME, Electric Research Institute, EPRI TR , November Available at 15 User s Guide to the Complex Terrain Dispersion Model Plus Algorithm for Unstable Situations, US EPA, Atmospheric Research and Exposure Assessment Laboratory, Research Triangle Park, NC 27711, Report No. EPA/600/8-89/041, March Available on the EPA website: 8

10 In modeling stable to neutral conditions, a central feature of CTDMPLUS is its use of a critical dividing-streamline height to separate the flow in the vicinity of a hill into two separate layers. Flow in the upper layer has sufficient kinetic energy to pass over the top of the hill, while the streamlines in the lower layer are constrained to flow in a horizontal plane around the hill. In modeling unstable or convective conditions, the model relies on a probability density function (PDF) description of the vertical velocities to estimate the vertical distribution of pollutants. Hourly profiles of wind and temperature measurements are used by CTDMPLUS to compute plume rise, plume penetration, convective scaling parameters. In stable/neutral conditions, the profiles of turbulence data are used to compute dispersion parameter values at plume height. The model calculates on an hourly basis how the plume trajectory is deformed by each hill. The computed concentration at each receptor is then derived from the receptor position on the hill and the resultant plume position and shape. 9

11 2. METEOROLOGICAL DATA BASES 2.1 Flat and Simple Terrain. One year of hourly data for two sites were retrieved and processed. The two sites selected for this study are Pittsburgh, PA (WBAN [Weather Bureau-Air Force-Navy] station No ), representative of an urban eastern site; and Oklahoma City, OK (WBAN station No ), representative of a southwestern plains site. The 1964 data are used at the Pittsburgh site and 1984 data are used at the Oklahoma City site. ISCST3 meteorological data were preprocessed by PCRAMMET and AERMOD meteorological data were preprocessed by AERMET AERMET Overview. AERMET 10 provides a general purpose meteorological preprocessor for organizing available meteorological data into a format suitable for use by AERMOD. National Weather Service (NWS) hourly surface observations and twice-daily upper air soundings, plus site-specific data from a meteorological measurement program can be processed in AERMET. There are three stages to processing the data. The first stage extracts meteorological data from archive data files and processes the data through various quality assessment checks. The second stage merges all data available for 24-hour periods (NWS and site-specific data) and stores these data together in a single file. The third stage reads the merged meteorological data and estimates the necessary parameters for use by AERMOD. Two files are written for AERMOD: 1) a file of hourly boundary layer parameter estimates; and, 2) a file of multiple-level observations (profiles) of wind speed and direction, temperature, and standard deviation of the fluctuating horizontal and vertical components of the wind. Input data used in this part of the study include: 1) hourly specification of wind speed; 2) hourly specification of wind direction; 3) hourly ambient temperature; 4) hourly solar radiation 16 ; 5) hourly cloud cover values; 6) a quantification of surface characteristics (surface roughness, albedo, Bowen ratio); and 7) twice-daily upper air soundings 17. Output includes hourly values for mixing heights and Monin-Obukhov lengths, surface friction velocity, convective velocity scale, and profiles of wind speed and direction, temperature and turbulence. Table 2-1 lists the albedo, Bowen ratio, and surface roughness that are assumed for this analysis. Table 2-1 lists only the rural settings for the meteorological data. The urban analysis is accomplished by setting the urban mode and urban source option in AERMOD and using the rural meteorological data for the model inputs.. 16 Solar and Meteorological Surface Observation Network , Version 1.0, US Department of Commerce, National Climatic Data Center, Asheville, NC / US Department of Energy, National Renewable Energy Laboratory, Golden CO, September Radiosonde Data of North America , Version 1.0, Forecast Systems Laboratory, Boulder, CO and National Climatic Data Center, Asheville, NC, August

12 Table 2-1. Albedo, Bowen Ratio, and Surface Roughness length assumed for AERMET preprocessor. Site Option Albedo Bowen Ratio Surface roughness (meters) Pittsburgh Rural Oklahoma City Rural PCRAMMET Overview. The PCRAMMET 18 model requires the twice-daily mixing heights and NWS surface observations. Prior to being made available, the data were checked for blank fields (missing data) and filled by accepted procedures. A modification was made to the data sets by setting the minimum mixing heights to 10 meters. This change was made to avoid spuriously high or low concentrations for the short stacks. Only the meteorological data used for the ISCST3 analysis was affected. For ISCST3, the minimum input data requirements to the PCRAMMET are the twice-daily mixing heights and hourly surface observations of wind speed, wind direction, dry bulb temperature, opaque cloud cover and ceiling height. The operations performed by the PCRAMMET include: 1) calculation of hourly values for atmospheric stability from meteorological surface observations; and, 2) interpolation of twice-daily-mixing heights to hourly values. A brief description of the meteorological data for the two sites is given in Table 2-2. Table 2-2. Missing soundings and calm wind conditions by site and year. Site Year Anemometer height (feet) Hours/ year Missing Soundings 0000 GMT GMT Calm wind conditions Pittsburgh Oklahoma City PCRAMMET User s Guide, US EPA, Office of Air Quality Planning and Standards, RTP, NC 27711, EPA-454/B , October Available from EPA's world-wide-web site at 19 GMT = Greenwich Mean Time 11

13 2.2 Building Downwash. Only the meteorological data from Pittsburgh (1964), as described in the preceding section, is used in the building downwash scenarios. No modifications were made to the data because there are no short stacks, (i.e. less than 20 meters) in this part of the analysis. 2.3 Complex Terrain. The meteorological data base used in the complex terrain portion of this study is taken from a project where site-specific data were collected 20. A 100-m tower, instrumented at 10, 50, and 100 meters and sodar equipment were used to gather the meteorological data. The sodar data was collected at 50-meter intervals, and the meter sodar data were used with the tower data to construct the meteorological profiles. The use of sodar turbulence data is limited to vertical turbulence values only. All of the tower and sodar levels are used in AERMOD and CTDMPLUS runs. Only the 100-m tower data (wind speed and wind direction) are used in ISCST3 runs (see Figure 2-1 for the 100 meter wind rose). The atmospheric turbulence and dispersion for ISCST3 are addressed by applying atmospheric stability classifications which are estimated by the solar radiation/delta-t (SRDT) stability scheme 21. To confine the differences between CTDMPLUS and AERMOD to differences in the dispersion algorithms, the METPRO 22 output used for CTDMPLUS (including the boundary layer parameters) is reformatted in a mode compatible with AERMOD meteorological data requirements. However, the predicted concentrations are not sensitive to these boundary layer values because profiled meteorological data are available at several levels straddling the stack release heights. 20 The data came from an unnamed source. 21 An Evaluation of A Solar Radiation/Delta-T Method for EstimatingPasquill-Gifford (P-G) Stability Categories", EPA-454/R , October User s Guide to the CTDM Meteorological Preprocessor Program, EPA-600/ , Available on the EPA website: 12

14 13

15 3. MODEL OPTIONS AND SOURCE DEFINITIONS 3.1 Modeling Options for Flat, Simple and Complex Terrain. The regulatory dispersion model used in this study for the flat and simple terrain is the ISCST3 model. The model was run in the regulatory mode which uses the option settings as described in Table 3-1. Table 3-1 also shows the parallel settings or options used for AERMOD setup. Table 3-1. Model Options Used in Consequence Analysis. ISCST3 AERMOD * Use stack tip downwash * Use stack tip downwash * Use buoyancy-induced dispersion * Use buoyancy-induced dispersion (not an option) * Do not use gradual plume rise (gradual plume rise is used in complex terrain) * Use gradual plume rise (not an option) * Use the calms-processing routines * Use the calms-processing routines(not an option) * Use default wind profile exponents * Calculate wind profiles (not an option) * Use default vertical potential temperature gradients * Calculate vertical potential temperature gradients (not an option) The results reported in these 2 components of the study are the high and the highest secondhigh concentrations averaged over 1-hr, 3-hr and 24-hr short term averages and the high annual average. 3.2 Source Characteristics for Flat, Simple Terrain. Ten source types are processed for the flat terrain part of this study: seven point sources, one area source and two volume sources. Source characteristics for each source type are presented in Table 3-2. The very buoyant 35 meter stack source and the 200 meter stack source in Table 3-2 are used in the simple terrain part of this study. All these sources are evaluated using: 1) both the rural and urban settings; and 2) both sets of meteorological data. Thus, there are 48 scenarios [(10 flat terrain sources + 2 simple terrain sources) x 2 land use settings (rural, urban) x 2 meteorological sites] and 7 different maximum concentration values for a total of 336 cases. 14

17 3.3 Source Characteristics for Complex Terrain. The complex terrain analysis examines a combination of four hills, two stack heights, two buoyancies, and two source-hill distances. The four hills are: 1) Piedmont, a hill near Keyser, WV; 2) Montour Ridge - Crosswind, near Sunbury, PA; 3) Montour Ridge - Alongwind; and 4) Cinder Cone Butte, located near Boise, ID. Except for "Montour Crosswind", the sources are located to the west of the hill centers, at distances of about 1 kilometer for the "close-in" case and about 10 kilometers for the "far-out" case (See Appendix B for the figures describing the hills). For "Montour Crosswind", the sources are located to the north of the east-west oriented ridge. The meteorological data base used in this study features a high percentage of winds from the northwest quadrant (see Figure 2-1). Therefore, the modeling results reflect a large number of cases of plume transport from the hypothetical sources to these hills. The source parameters for the complex terrain analysis are provided in Table 3-3. Although there are 32 possible combinations of hill/source/source-hill distances ( 4 hills x 2 stack heights x 2 buoyancies x 2 source hill distances), the plume never significantly impacts the Cinder Cone Butte hill in 4 of the cases and are not included in the analysis. Thus, the results are reported for a total of 28 complex terrain cases. 3.4 Source Characteristics for Building Downwash. A series of hypothetical scenarios involving single point sources and rectangularly shaped buildings were chosen in an earlier work and these configurations are retained for this study. ISCST3, ISC-PRIME and AERMOD are applied to each scenario. The test cases include the following situations: * a stack adjacent to a building structure, and also four building heights away from the northeast corner of the building; * stack height to building height ratios of 1.0 and 2.0; * squat, supersquat, and tall building shapes; and, * urban and rural settings. A no-building set of cases is also used for "control" runs. Not counting the no-building cases, there are 20 source/building scenarios and three averaging times to provide a total of 60 cases in this component of the study. The selection of this set of source configurations and averaging times matches that of the earlier consequence analysis. The stack parameters are listed in Table 3.4. One year of meteorological data (Pittsburgh, 1964) is employed in this analysis. The results for the highest second-highest 3-hour and 24-hour concentrations, as well as the highest annual concentration are tabulated for each run. The analysis also includes the model predictions for the highest 1 hour cavity concentration. 16

18 Table 3-3. Complex Terrain Source Configurations. Stack height - Buoyancy Emission rate (g/s) Stack Height (m) Stack Gas Temperature (K) Exit Velocity (m/s) Stack Diameter (m) Low/Low Low/High High/Low High/High Table 3-4. Source characteristics for building downwash analysis - point sources. Stack height (m) Emission rate (gs -1 ) Exit velocity (ms -1 ) Stack diameter (m) Temperature (K) Receptor Configuration for Flat and Simple Terrain A gridded polar array of receptors is used in the flat terrain portion of the analysis. For the point sources, there are 36 radials (beginning at 10 degrees from north and spaced every 10 degrees). The distance of the concentric rings are: 125m, 250m, 400m, 800m, 2000m, 4000m, 8000m, and 16000m. The volume and the area source polar grid is also set up for 10 degree radials but uses concentric ring distances of 125m, 250m, 400m, 800m, and 2000m. A gridded polar array of receptors is used for the point sources in simple terrain settings. There are 36 radials (beginning at 10 degrees from north and spaced every 10 degrees). The distance of the concentric rings were: 800m, 2000m, 4000m, 7000m, and 15000m. The elevations for the receptors are plotted (with isopleths) in Figures 3-1 (35 meter stack) and 3-2 (200 meter stack). 17

19 3.6 Receptor Configuration for Building Downwash. A cartesian receptor grid extending out to 10 kilometers is used in the building downwash analysis. The receptor density varies, with 50-m spacing for the first 500 meters, 100 m spacing out to 1000 m, 200 m spacing out to 2000 m and 1000 m spacing out to m. This spacing matches that used in the original ISC-PRIME consequence analysis. 3.7 The Complex Terrain Receptor Locations. The Figures in Appendix B show the contours of the hills used in the analysis. AERMOD, ISCST3, and CTDMPLUS are run with the full year of data described above for 28 combinations of sources, and source-hill distances (1 and 10 kilometers). The CCB and Montour longwind/crosswind setting includes a total of 140 receptors; the Piedmont Hill setting uses a total of 144 receptors; and, the Cinder Cone Butte setting uses 140 receptors. Appendix C contains the input files used to run AERMOD and provides the location and elevations of all the receptor locations for all runs. In all cases, each model estimates concentrations on single hills downwind from the source. 18

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